Overview: Shadow AI is an agent which is powered by the LLM (Large Language Model) in our case LLAMA 2 (specifically, llama-2-7b-chat model). The Agent is designed to help his boss in an efficient way for Drafting Emails Searching a Document and providing relevant information and tasks which are asked. Generating the presentation content Boss Mode: Combining all the crucial information and providing it to the boss. (Jus like Jarvis) The agent specifically provides a combination of all the stuff listed above and specifically lists them. The agent is also able generate the relevant images with the help of stable-diffusion Key Technology: AWS Sagemaker (Our agent extensively uses the AWS sagemaker) For running the llama-2-7b-chat model For running the stable-diffusion-v2-1-base AWS Lamda For communication with our models AWS API Gateway For providing the Api access AWS S3 For storing the objects and the frontend Python 3 Details: We are using AWS’s sagemaker service for running the LLM model and the stable diffusion model. Using AWS’s sagemaker we can run the model with ease. The models are then interacting with the help of AWS’s Lamda function which is also authenticated. All the object is stored at AWS’s S3 bucket and then used on the front-end

"StableReverse" is an app that empowers users to explore, comprehend, and analyze Python code repositories hosted on GitHub. This innovative project simplifies the challenging task of reverse engineering code by offering a comprehensive suite of features and an intuitive interface, making it accessible to a broad spectrum of users, from experienced developers to data scientists and curious learners. StableReverse leverage GPT3 for analyzing the repo filse system and StableCode for writing the code. Use Cases: Code Debugging: Developers can use "StableReverse" to understand and debug unfamiliar code segments, identifying issues and improving software quality. Algorithm Exploration: Data scientists and researchers can explore complex algorithms and data processing techniques implemented in open-source projects. Learning Tool: Students and learners can gain insights into coding practices by studying and reverse engineering real-world code. Open-Source Contribution: Contributors to open-source projects can quickly grasp project structures and coding conventions. Code Auditing: Security experts can use "StableReverse" to identify potential vulnerabilities and security issues in codebases. Innovation Exploration: Innovators and entrepreneurs can explore existing codebases for inspiration and to understand emerging technologies.

AI-SteerEDU aims to revolution the world of online Platforms by giving the opportunity to give feedbacks from the individuals. The learners can also ask question in different languages to get responses in same Language. Suppose he gives feedback in French then the response will also be in French. Llama 2 gives us the opportunity to train Custom datasets on their own models to get specified results. Our main aim to collect feedbacks from students for online learning coaching platforms and refer other students the same courses according to their interests. Online learning platforms are used by millions of students worldwide, but finding the right courses and materials can be overwhelming. Our challenge is to create a personalized recommendation system that helps learners discover relevant courses and resources effectively.